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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 17, issue 7
Hydrol. Earth Syst. Sci., 17, 2947–2966, 2013
https://doi.org/10.5194/hess-17-2947-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 17, 2947–2966, 2013
https://doi.org/10.5194/hess-17-2947-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 25 Jul 2013

Research article | 25 Jul 2013

Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances

T. Conradt1, F. Wechsung1, and A. Bronstert2 T. Conradt et al.
  • 1Potsdam Institute for Climate Impact Research, Potsdam, Germany
  • 2Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany

Abstract. A problem encountered by many distributed hydrological modelling studies is high simulation errors at interior gauges when the model is only globally calibrated at the outlet. We simulated river runoff in the Elbe River basin in central Europe (148 268 km2) with the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model). While global parameter optimisation led to Nash–Sutcliffe efficiencies of 0.9 at the main outlet gauge, comparisons with measured runoff series at interior points revealed large deviations. Therefore, we compared three different strategies for deriving sub-basin evapotranspiration: (1) modelled by SWIM without any spatial calibration, (2) derived from remotely sensed surface temperatures, and (3) calculated from long-term precipitation and discharge data. The results show certain consistencies between the modelled and the remote sensing based evapotranspiration rates, but there seems to be no correlation between remote sensing and water balance based estimations. Subsequent analyses for single sub-basins identify amongst others input weather data and systematic error amplification in inter-gauge discharge calculations as sources of uncertainty. The results encourage careful utilisation of different data sources for enhancements in distributed hydrological modelling.

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